This DSEIS essentially used the same modeling and analysis systems used to do the Sierra Nevada Framework Project. Therefore, this appendix will only describe items that were differences from those used to produce the Final EIS for SNFPA and the reader can find a more detail description of the techniques and assumptions in Appendix B of the FEIS. This analysis, like the in FEIS, is based on a multi-scale and hierarchical modeling approach to analyze the various alternatives developed by the management team. The analysis was accomplished by using a suite of different optimization, visualization, and simulation models to make projections of how the National Forests within the Sierra Nevada Framework region would respond to different disturbances and management events. Due to the complexity and magnitude of this project, the use of multiple models and development of a analytical support system was required to integrate these processes.

The analysis uses data from forest inventory plots, GIS-based resource inventories, vegetative simulation models, operations research decision analysis techniques, and mapping and data visualization tools to support decision-making. Vegetative prescriptions, management activities, and disturbances events are assigned to specific types of land areas (allocations), and the resulting effects on forest outputs and environmental consequences including vegetation structure, wildlife suitability, and fuel conditions are evaluated.

Results from the modeling effort are only approximations of what to expect when any given alternative is implemented. The objective of modeling is to aid planners in estimating likely future consequences of alternative management actions. A choice between alternatives can be made even though the model may lack precision in describing specific attributes of a given alternative. The planning models used have many internal limitations and parameters. These limitations must be considered when analyzing the outputs and effects projected by these models. Once the EIS models were formulated, a number of sensitivity tests were made to check for reasonableness and to make calibrations to coefficients whose development was not based on empirical data or where development of coefficients was not exactly straightforward. Since many of the Standards and Guidelines are not easily put into a mathematical formulation, it is important that model outputs satisfy the intent of the ID Team and the Standards and Guidelines themselves. This was done through an iterative process involving all of the ID Team and key management members and those responsible for developing the component models.

The analysis process was based on close integration of GIS, fire simulation, and forest inventory data with traditional vegetative growth and yield modeling in essential a single process which allows users to:

define spatially explicit management allocations, constraints (S&Gs), and priority units using GIS technology,
link these management units to forest inventory information,
simulate and evaluate hundreds of thousands of possible management activities, while tracking over 50 resource variables through time,
provide insight on policy or management alternatives with different sets of desired future conditions and standards and guides,
select an "optimal mix" of treatments to achieve a balance among a broad range of often conflicting management goals and desired future conditions,
evaluate alternative management strategies using sophisticated mapping, reporting, and data visualization or rendering tools,
links various resource data and models into an integrated system, enabling analysis of both terrestrial and aquatic ecosystems, and
declare spatially explicit delineation of areas where land management activities and resource protection measures will be meaningfully.

National Forest Land and Resource Management Plans and amendments to these plans are themselves models of land management through time. The plans attempt to simulate actions (for example, management activities such as vegetative intervention and road decommissioning) and project environmental consequences from these actions. Not all resources and factors can be considered and addressed in a plan. Plans and analysis attempt to that mimics, in a simplified fashion, what might happen through time. Similarly, none of the models described below can perfectly represent the "real world" situation. Therefore, the results from these models are only approximations to the outcomes that can be expected if the alternatives are put into action. The purpose of these models is to provide insight and clarify knowledge. In many cases, these approximations are fully adequate to compare alternative strategies or reject those that are not feasible or reasonable. A choice between alternatives can be made even though the models may lack the precision to describe the behavior of specific attributes of a given alternative. In other words, the models reveal relative differences between alternatives more reliably than absolute differences. These models make projection of future conditions under a given set of assumptions and not prediction of future conditions.

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USDA Forest Service · Pacific Southwest Region